This paper introduces a novel method called SMR which integrates summary data from GWAS and eQTL studies to identify genes whose expression level is associated with complex traits through pleiotropy. This method can be used to prioritise putative causal genes at GWAS loci for follow-up functional studies. The main features are
1) It uses summary data so that the power is maximised by using data from the latest large-scale GWAS and eQTL studies.
2) The method is based on Mendelian randomisation analysis so that any gene-trait association identified by this analysis is free of confounding from non-genetic factors.
3) It uses a heterogeneity test (HEIDI test) to distinguish pleiotropy or causality (a single genetic variant affecting both gene expression and the trait) from linkage (two distinct genetic variants in LD, one affecting gene expression and one affecting trait).